App for Google Glass recognises people by their dress

Google has not yet released the Explorer edition of the awesome wearable technology, Google Glass. The company will be shipping these devices to only those people who were lucky enough to win the “IF I Had Glass” contest conducted by Google. We have got a few applications already. For example, JetBlue showcased five concepts for Google Glass for the contest, and all the five were awesome.

Today, we have a new application idea from a group at Duke University. The group has come up with a concept in which the Google Glass will help you identify your friends in a crowd. And this will not be using the conventional face recognition technology, but a new technology which will identify the clothes your friends are wearing. This new app is called InSight.

Imagine a near future where humans are carrying smartphones and wearing camera-embedded glasses, such as the Google Glass. This paper intends to recognize a human by looking at him or her from any angle, even when her face is not visible.

Even if the people you are looking for have turned their back, the app will be able to recognize them with just their clothes. And in a room full of people, the app will be able to give name tags to all the people in the room. Would this be something like the name tags that we see on our teammates in a single person shooter? Well, I am not sure of that, but it is really interesting. And in situations where names are not suitable, users could share a tweet such as “looking to share a cab.”

For instance, Alice may look at people around her in a social gathering and see the names of each individual – like a virtual badge –suitably overlaid on her Google Glass display.

Where revealing names is undesirable, only a tweet message could be shared. People at the airport could tweet “looking to share a cab ”, and Alice could view each individual’s tweet above their heads. In general, we intend to extend augmented reality [1, 2] to humans and the key challenge pertains to differentiating individuals. We explore options outside face recognition [3, 4]

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